Data fusion

Combine multiple sources to
increase the accuracy of data

Bridge the gaps in AI fusion by using reliable, tested human intelligence combined with automated scaling.

Combine multiple datasets

Solve the issues and discrepencies in combining datasets at scale

Align different sources

Gain a deeper understanding by analysing in multiple ways

Gain a new perspective

Discover new insights by looking from many different angles

Solve complex problems

Enable unique analysis techniques to tackle the hardest questions

Data fusion provides
new ways to look at data

Being able to combine multiple datasets makes for better decisions, especially when they are from entirely different sources. As well as cross checking results, it provides a new perspective to gain fresh insights and allows for a greater level of detail.

However, combining data sources comes with inherent friction, they often don’t line up correctly and decisions have to be made. We use human judgement to bridge the gap when aligning datasets and then automate this understanding to scale your fusion efforts.

One solution,
all your data types

Image detection

Detect objects and add context to analyse imagery

Shape recognition

Detect and categorise shapes and patterns in imagery

Video enhancement

Categorise, label and annotate video in real time

Boundary & route analysis

Understand and map out boundaries and routes

Scale your labelling with no compromise on quality

A core challenge of data labelling is scaling your team. While small pools of workers can’t handle large datasets and increase the risk of individual error, large pools are hard to manage and likely to be less focused or knowledgable.

We have a ten year track record of using existing pools to take the weight of crowd management off your shoulders of world class companies. Participant input is statistically weighted based on their track record to combining the results of many workers for any given task and ensure the highest quality results.

Focus on unique problems with high level configuration

We provide well-tested solutions that can be rapidly implemented for more straight forward tasks, helping you focus on the more important and high impact work.

For more difficult tasks, unknown problems or new areas of research, our flexible internal toolkit and extensive experience in crowd labelling allows us to design and deploy workflows which focus crowd effort onto your specific problem. No more generic ‘place a bounding box’ results.

Labelled data from 1715 Labs helped our model improve robustness and consistency on real world noisy documents

Lorenzo Bongiovanni - Lead Machine Learning Scientist @ Amplyfi

1715 Labs' human-led approach unlocks hard to reach value in complex datasets

Derek Langley - Product Line Design Authority @ Thales
Trusted by data teams at

Contact us to
get your AI out of the lab

We'll guide you through the best solution and implementations to achieve your data goal and make the most of your artificial intelligence.